An Active Vision detection method and system for detecting credential stealing attacks using an automated machine-learning page examination engine is provided that may be used to detect both brand-based and custom credential stealing attacks. The approach employs similarity analysis in a two stage process that may be achieved through supervised or self learning machine learning techniques and is comparable to human analysis. The Active Vision System is capable of self-learning; every new attack detected by the system becomes part of system's long term memory making it incrementally more accurate in future predictions using its past experience.